1. Field of the Invention
The present invention relates to an MFA (Metabolic Flux Analysis) information system using XML (eXtensible Markup Language) and an operating method thereof. More specifically, the invention relates to an MFA information system and an operating method thereof, which generates, edits stores and visualizes an MFA model feature and an MFA object using XML, and edits, stores and visualizes the result obtained by performing MFA based on the object.
2. Background of the Related Art
MFA is one of mathematical modeling techniques and simulations which are widely used. The mathematical models can be largely divided into a model including dynamic and regulating mechanism information and a model considering only the stoichiometry of biochemical reactions. The dynamic model predicts internal variations in a cell with the passage of time to accurately describe the dynamic state of the cell. However, it has a shortcoming of requiring lots of dynamic parameters.
MFA obtains an ideal metabolic flux space that cells can reach using only a set of metabolic mass balancing reactions and cell composition information. It is known that MFA can show the ideal metabolic fluxes without requiring dynamic information and satisfactorily describe or estimate behaviors of the cell (Edwards et al., The Journal of Biological Chemistry, 274, 17410-6, 1999; Nielsen, et al., Bioreaction Engineering Principles, Plenum Press, 1994).
MFA is a mathematical approach to detect variations in metabolic fluxes with the stoichiometry of metabolic reactions and the measurements of produced and consumed quantities of various metabolites. MFA is based on the quasi-stationary state assumption. It means that a variation in the concentration of metabolites in a cell could be ignored and the concentration could be constant because the variation in the concentration of the metabolites in a cell caused by external environment modifications is very immediate.
If all metabolites and metabolic pathways and stoichiometric matrix in each pathway (SijT, metabolite i in the jth pathway) are known, a metabolic flux vector (vj, flux of the jth pathway) can be calculated. A variation in a metabolite X with the passage of time can be represented by the sum of all metabolic reaction fluxes. When it is assumed that the variation in the metabolite X with the passage of time is constant, that is, on the assumption that metabolic reaction is under the condition of the quasi-stationary state, the variation in the metabolite X is defined as follows.STv=dX/dt=0
However, this equation is expanded to the following equation because only pathways are known and stoichiometric value (for each metabolite and pathway) and metabolic flux (vj) are partially known in most cases.STv=Smvm+Suvu=0
This equation is divided into two matrixes; One is the matrix defined as the inner product of an experimentally known stoichiometric value (Sm(I×M), I is a total metabolic number and M is a total stoichiometrically-known reaction number) and a flux (vm(M×I)). The other is the product of an unknown stoichiometric value (Su(I×M)) by a flux (vu(M×I)).
Here, when rank (Su) of the unknown flux vector (Su) is identical to or larger than U (that is, when the number of variables is identical to or smaller than that of the equation), the flux is obtained through matrix calculation. However, when rank (Su) of the unknown flux vector (Su) is larger than U (when a duplicate equation exists), an operation of checking consistency of all equations, accuracy of flux measurement values and propriety of quasi-stationary state is performed in order to calculate more precise values.
If the number of variables is larger than that of the equation, a unique optimum metabolic flux distribution is obtained using linear optimization that uses various physical and chemical constraints, such as restricting a specific metabolic flux value within a specific range etc., and a specific objective function, which is defined as follows.minimize/maximize: Z=ΣCiViS.t. STv=0 and amin,i≦Vi≦amax,i 
Here, Ci represents a weight and Vi denotes a metabolic flux vector. Cell growth maximization, metabolite production maximization and by-product production minimization are generally used as the objective function.
MFA can be used for calculating the maximum production yield of a desired metabolite through which characteristic of a metabolic pathway inside a cell can be detected. When the characteristic of the metabolic pathway is grasped, a metabolic pathway required to be operated is detected and metabolic flux is operated using the most effective method by a strategy for operating the metabolic pathway, thus making it possible to produce a desired metabolite.
To handle these MFA elements, metabolic network information including metabolites, metabolic pathways and stoichiometric matrix in each pathway and metabolic condition information including metabolic flux measurement values, genetic and environmental conditions and physical and chemical constraint conditions are required.
There have been systems for generating, editing, storing and visualizing the aforementioned information. However, a system for generating, editing, storing and visualizing the information using XML that is a standard of data and documents on the Internet has not been reported yet. Although there was an attempt to insert annotating simple condition information into an XML structure, it only dealt with the information on the flux limits associated with each flux and there was no detailed reference for an XML schema structure and thus it was not easy to actually utilize (Segre et al., A Journal of Intergrative Biology, vol 7, 301-16, 2003).